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Health Informatics and Bioinformatics

Since Electronic Health Record (EHR) systems are mission-critical to healthcare delivery organizations and must be integrated with their plethora of other information systems, there are emerging tools for innovation adding value and convenience the sometimes inflexibility and challenging user interfaces of current EHRs. The most promising candidate to serve as such a platform is SMART on FHIR. A growing number of institutions are using SMART on FHIR to innovate on top of commercial EHRs. Granted, some of the commercial EHR systems (e.g., Epic) currently support the Fast Health Interoperability Resources (FHIR) standard incompletely, but as SMART on FHIR matures, this will be a great platform for apps that read and write data from the EHR.

Especially Clinical Decision Support (CDS) that ties in with Patient Safety and efficient (“Lean”) healthcare delivery as well as various ways to support Population Health Management seem to be prime candidates for app development. CDS is understood here as knowledge and person-specific information, intelligently filtered or presented at appropriate times to improve healthcare decisions. So far, CDS enjoyed partial successes in selected areas within the US healthcare system. For example, its role in reducing care costs and improving care quality as well as positively impacting healthcare providers’ performance with drug ordering and preventive care reminder systems is well established, however, most likely only because this type of CDS relies on a minimum of patient data that are readily available before the advice is generated. The difficulty to access appropriately selected information from the entire patient record, for instance, due to distribution on different providers electronic health records or the lack of integration between clinical and administration systems, may be one important reason that it has not realized its anticipated potential to transform healthcare. With the advance of SMART on FHIR and CDS hooks, big data technologies and artificial intelligence (AI), CDS in healthcare is changing, but new challenges arise. For instance, the question on how to transform big data into accessible “smart data” has attracted commercial players like IBM Watson Health or inspired the exploration of the use of blockchain technology for electronic health records. There a need for high-quality and effective ways to design, develop, present, implement, evaluate, and maintain various types of clinical decision support capabilities for clinicians, patients and consumers. These issues need to be resolved before patients and organizations can begin to realize the maximum possible benefits of these systems. This may include not only technological issues, but also for example the exploration of the potential of AI to reduce the cognitive burden of the user of the technology.

Our faculty have decades of experience in healthcare (surgery, hepatology, nursing, patient safety, lean healthcare), computer science (artificial intelligence, machine learning, data mining, security, privacy, visualization, text mining, blockchain technology and app development), data science (“Big Data”) and information systems as well as integrating the user perspective into informatics projects. With our unique approach in creating interprofessional teams we feel very well positioned to help physicians, healthcare providers and organizations to enhance their EHR and information systems to improve patient safety and decision support or even support APMs or population health management, to name only a few examples. Please don’t hesitate to contact us with any questions or ideas you might have.